[Analysis of Coronavirus Disease 2019 Prediction Studies in the Republic of Korea].

Objectives: During the initial outbreak of coronavirus disease 2019 (COVID-19), numerous predictive studies were conducted amid high uncertainty regarding the characteristics of the virus, and the study results were considered in the policymaking process. Methods: This study systematically analyzed research papers that predicted the spread of COVID-19 in the Republic of Korea. Focusing on 138 studies published between 2020 and October 15, 2024, it examined the data and methodologies employed and explored ways to enhance the utility of predictive outcomes in managing infectious disease outbreaks. Results: These methodologies included mathematical models, statistical models, and machine learning-based approaches to predict COVID-19 spread patterns. Beyond forecasting future outbreak trends, these predictive models were also instrumental in evaluating existing measures and proposing effective policies through scenario-based assumptions. Conclusions: This study's findings highlight the importance of multidisciplinary collaboration in developing predictive models to effectively prepare for and respond to infectious diseases. By doing so, it aims to minimize the public health impacts of infectious diseases.